There are gender wars, and then there are casualties. It wasn’t until 2011 that the behemoth toymaker LEGO acknowledged girls’ desire to build with bricks, even though the company had long before made a seemingly effortless pivot to co-branding, video games, and major motion pictures. So it’s little wonder that girls face all-too-real obstacles when […]Read more
“Being able to teach machine learning to tens of thousands of people is one of the most gratifying experiences I’ve ever had,” says Stanford University computer science professor Andrew Ng.
Over 100,000 students signed up for his free, fall 2011 course on machine learning. The impacts were huge. Over 12% of the students completed the course, and received a statement of accomplishment. Ng says he “heard many stories from students about how they’re using it at work, about how it’s inspired them to go back to school, and so on.” In contrast, Ng’s normal, for-credit course at Stanford, one of the most popular on campus, would enroll 350 students.
It’s part of a new revolution in higher education, and it’s serious learning. They deliver complete courses where students are not only watching web-based lectures, but also actively participating, doing exercises, and deeply learning the material. Students are expected to devote ~12 hours a week to the course, to read and watch course materials, complete assignments, and take quizzes and an exam. Online students did not receive one-on-one interaction with professors, the full content of lectures, or a Stanford degree — those who completed the course received a statement of accomplishment. Course materials include prerecorded lectures (with in-video quizzes) and demos, multiple-choice quiz assignments, automatically-checked programming exercises with an interactive workbench, midterm and final exams, a discussion forum, optional additional exercises with solutions, and pointers to readings and resources.